Predicting Epidemic Size
Project pitch
Real outbreaks typically do not spread as pervasively as would be predicted from simple dynamical models. Reasons for this include population heterogeneity, population structures (unknown effective number of susceptibles), and behaviour change. Participants will discuss how to define epidemic “size”, and how to measure key parameters that affect it. They will construct simulations to explore the expected effects of changes in these parameters. They will then fit data from simulations and investigate the extent to which it is possible to estimate and disentangle these various effects. Participants may proceed to apply their findings to estimates of heterogeneity and uncertainty in real outbreaks (for example, the current BVD outbreak).
Research area(s)
- Infectious disease dynamics
- medium-term forecasting
Data
- Simulated and possibly real data
- Public archives
- Participants can choose relatively clean or messy data depending on particular research interests
Software
Participants will use methods in R similar to those employed during the workshop.
Potential research question(s)
- What are the key parameters underlying epidemic size?
- Can we improve assessment of potential epidemic size for new and re-emerging pathogens?